Justin Gottschlich

CEO & Chief Scientist @ Stealth Inc. (details forthcoming)

Ex-Principal AI Scientist & Director/Founder of Machine Programming Research (Intel Labs)

Ex-Principal Investigator and Founder of the upcoming Intel/NSF Machine Programming Research Center

Steering Committee Chair, ACM SIGPLAN Machine Programming Symposium (MAPS)

Chair of Industrial Board and Executive Director at PRECISE, University of Pennsylvania

Adjunct Assistant Professor & Co-Director of Master of Science in Engineering (Embedded Systems Program), University of Pennsylvania (my Penn website)

Highlights

My Machine Programming & Technology YouTube Channel (subscribe & stay updated)

Keynote at LADSIOS (co-located with VLDB '21): "Machine Programming and the Future of Software Development"

New demo of one of our production quality MP systems: AutoPerf

Our team, joint w/ MIT & Microsoft, won two awards at SIGMOD '21!

Keynote @ MIT's DSAIL 2021 virtual retreat: "A Glimpse Into Machine Programming @ Intel Labs"

Invited talk @ UWisc's 2020 MLOS Seminar Series: "Machine Programming: Challenges and Opportunities" (video)

Keynote @ Penn's PRECISE 2019 Industry Day: "Machine Programming: The Future of Autonomy"

Our research has been highlighted by venues like Wall Street Journal, DeepLearning.ai, Communications of the ACM, New York Times, SDTimes, Economic Times, Venturebeat, and Wharton, and many others.

Students

Roshni Iyer (advised by Yizhou Sun and Wei Wang @ UCLA)

Ramneet Kaur (co-advised with Insup Lee @ Penn)

Fangke Ye (advised by Vivek Sarkar @ Georgia Tech)

Recent Committees

ICLR'22, PLDI'22, CGO'21, NeurIPS'21, AIDB'21, PACT'21, FSE'21, OOPSLA'21, MAPS'21 (SC chair), ICML'21, USENIX ATC'21, ICLR'21, MLSys'21, NeurIPS'20, MAPL'20 (SC chair), JPDC'20, aiDM '20, TheWebConf'20, MLSys'20, PACT'19 (SRC), SysML'19, MAPL'18 (general chair)

Contact: justin.gottschlich@gmail.com

Brief Biographical Sketch

I founded and lead the Machine Programming Research group at Intel Labs. Machine programming (MP) is a new field of research that uses automation to reduce the temporal constraints of software development (e.g., the time it takes a developer to write, maintain, and test code) and improve software quality characteristics (e.g., performance, correctness, security, maintainability, etc.). We generally consider MP as a fusion of machine learning and formal methods, which rely heavily on programming languages and systems. We provide a brief overview of MP in our “Three Pillars of Machine Programming” vision paper (see Armando Solar-Lezama's website for a deeper dive). In academia, I have appointments as the industrial advisory board chair and executive director for the PRECISE Center at the University of Pennsylvania (Penn). I am also an adjunct assistant professor at Penn in the Computer and Information Science Department.

I have a deep desire to build bridges with thought leaders across industry and academia to identify disruptive research and push it forward as a community. Recently I have been working with Amazon, Brown, Georgia Tech, Google AI, Hebrew University, IBM Research, Microsoft Research, MIT, Penn, Stanford, Texas A&M, UC-Berkeley, and UCLA, to name a few. I co-founded and was the principal investigator of the joint Intel/NSF CAPA research center which focuses on simplifying the software programmability challenge for heterogeneous hardware. I am the founder and principal investigator of the upcoming Intel Machine Programming Research Center (launching in 2022). I helped form the ACM SIGPLAN Machine Programming Symposium (MAPS) and currently serve as its steering committee chair. I have the honor of serving on the advisory board of Solar-Lezama et al.’s 2020 NSF Expeditions “Understanding the World Through Code” and Inteon, a machine programming venture fully-funded by Intel.

I have 40+ peer reviewed papers, 50+ issued patents, and 100+ patents pending. I've been lucky enough to have been invited to give talks at places like Berkeley, BMW, DARPA, IBM Research, MIT, Penn, Stanford, UCLA, University of Washington, VMWare, and Wharton, amongst others. I've had the tremendous honor to give keynote addresses at places like VLDB (LADSIOS), University of Pennsylvania, the US Department of Energy, and MIT. My team's research has been highlighted by venues like The Wall Street Journal, DeepLearning.ai, Communications of the ACM, MIT Technology Review, The New York Times, and many others.

My (extremely dated) CV is here. Google scholar.

Recent Activity

51st patent issued: "51: "Methods, systems, articles of manufacture and apparatus for code review assistance for dynamically typed languages" (11,157,384)

Keynote address at LADSIOS (co-located with VLDB '21): "Machine Programming and the Future of Software Development"

[Milestone] 50th patent issued: "Methods and apparatus to detect side-channel attacks"

49th patent issued: "Methods and apparatus to automatically generate code for graphical user interfaces"

48th patent issued:: "Efficient sharing and compression expansion of data across processing systems"

Our team, Machine Programming Research (MPR), won two awards at SIGMOD '21!

Accepted to the KDD Workshop on Programming Language Processing: "A Survey on Semantic Parsing for Machine Programming"

47th patent issued: "Methods and apparatus to improve utilization of a heterogeneous system executing software" (11,036,477)

46th patent issued: "Methods and apparatus to validate data communicated by a vehicle" (11,024,180)

MAPL (now MAPS) 2020 virtual workshop link

45th patent issued: "Methods and apparatus for recommending computer program updates utilizing a trained model" (11,003,444)

Accepted to the 2021 ACM SIGPLAN Machine Programming Symposium (MAPS): "ControlFlag: A Self-Supervised Idiosyncratic Pattern Detection System for Software Control Structures"

Accepted to the 2021 ACM SIGPLAN Machine Programming Symposium (MAPS): "Predictive Locality Optimization for Higher-Order Tensor Computations"

Accepted to 2021 GECCO Workshop on Evolutionary Computation Software Systems (EvoSoft): "AI Programmer: Autonomously Creating Software Programs Using Genetic Algorithms"

44th patent issued: "Extend GPU/CPU coherency to multi-GPU cores" (10,956,330)

43rd patent issued: "Methods and apparatus to detect memory leaks in computing systems" (10,956,298)

42nd patent issued: "Neural network optimization mechanism" (10,929,749)

41st patent issued: "Methods and apparatus for runtime multi-scheduling of software executing on a heterogeneous system" (10,908,884)

Upcoming keynote address @ MIT's DSAIL 2021 virtual retreat: "A Glimpse Into Machine Programming @ Intel Labs"

40th patent issued: "Compute optimization for deep neural networks" (10,902,547)

39th patent issued: "Coordination and increased utilization of graphics processors during inference" (10,891,707)

A video on our ControlFlag system

38th patent issued: "Systems and methods for determining a configuration of a microarchitecture" (10,853,554)

Former Students

MS advisor (University of Pennsylvania): Brad MacDonald -> Tesla

MS co-advisor (University of Pennsylvania): Celine Lee -> Intel Labs, then PhD student @ Cornell

PhD committee member (Lehigh University): PanteA Zardoshti -> Microsoft Research

PhD committee member (University of Washington): Maaz Ahmad -> Adobe Research

MS advisor (University of Pennsylvania): Akhilesh Gupta -> Apple

MS advisor (University of Pennsylvania): Sam Weintraub -> Outrider

PhD committee member (UT-San Antonio): Mohammad Mejbah ul Alam -> Intel Labs, Google

PhD committee member (Lehigh University): Wenjia Ruan -> Qualcomm

PhD co-advisor (Brown University): Irina Calciu -> VMWare Research